Multi-regional COVID-19 epidemic forecast in Sweden.

Area of Science:

• Epidemiology
• Biostatistics
• Public Health

Background:

• The COVID-19 pandemic highlighted the need for accurate infectious disease outbreak prediction.
• Existing methods may not adequately capture the spatiotemporal dynamics of disease spread.
• Forecasting epidemic occurrence probability is crucial for public health preparedness.

Purpose of the Study:

• To develop and apply a novel bio-system reliability approach for predicting epidemic outbreak probability.
• To determine the epidemic occurrence probability over various time horizons and regions.
• To benchmark state-of-the-art methods using real-world clinical data.

Main Methods:

• Application of a novel spatiotemporal health system reliability method.
• Direct analysis of raw clinical data, specifically daily COVID-19 patient numbers.
• Utilizing statistical methods for multi-regional health systems observed over time.

Main Results:

• Development and application of a novel spatiotemporal health system reliability method to COVID-19 data.
• Achieved accurate multi-regional prediction of epidemic occurrence.
• Provided epidemic threshold confidence bands for enhanced forecasting.

Conclusions:

• The developed methodology enables accurate prediction of epidemic outbreak probability for multi-regional biological systems.
• The approach is suitable for various public health applications using clinical survey data.
• This reliable long-term forecast aids in managing highly pathogenic virus outbreaks.